CN112529868B - Image analysis method, image analysis device, computer equipment and storage medium - Google Patents
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Abstract
The application relates to an image analysis method, an image analysis device, computer equipment and a storage medium. The method comprises the following steps: responding to the input operation instruction, and determining a brain region to be merged in the brain image to be analyzed; the brain regions to be merged comprise brain regions in different brain regions in the brain image to be analyzed; acquiring the characteristics of each brain region to be merged, and displaying the characteristics of each brain region to be merged on a brain region management interface; and carrying out merging operation on each brain region to be merged according to the characteristics of each brain region to be merged to obtain a first target brain region. By adopting the method, the first target brain region with higher accuracy can be obtained, and the obtained first target brain region comprises brain regions in different brain regions in the brain image to be analyzed, so that the brain regions in different brain regions in the brain image to be analyzed can be analyzed simultaneously when the obtained first target brain region is analyzed, the analysis of the first target brain region is more comprehensive, and the analysis accuracy of the first target brain region is improved.
Description
Technical Field
The present disclosure relates to the field of medical image technology, and in particular, to an image analysis method, an image analysis device, a computer device, and a storage medium.
Background
Diagnosis of cerebral neurodegenerative diseases such as Alzheimer's disease is a challenge for clinicians, especially at the early stages of the disease. With the development of brain function imaging techniques, imaging examinations such as computed tomography (Computed Tomography, CT) and magnetic resonance imaging (magnetic resonance imaging, MRI) can evaluate whether a change in brain anatomy has occurred, whereas positron emission tomography (Positron emission tomography, PET) can detect pathological changes earlier, which plays an important role in the diagnosis of brain neurodegenerative diseases.
In the traditional technology, the brain is divided into different cerebellum areas according to fixed rules on an imaging image through brain nerve analysis software, and the divided cerebellum areas are analyzed, so that the advanced nerve activity of each brain area of the brain is obtained. However, this approach does not yield accurate analysis of advanced neural activity of the brain when disease occurs between two brain regions, or when disease accumulation regions span multiple distinct brain regions.
Therefore, the conventional imaging data analysis method has a problem that imaging data cannot be accurately analyzed.
Disclosure of Invention
In view of the foregoing, it is desirable to provide an image analysis method, apparatus, computer device, and storage medium that can accurately analyze imaging data of imaging.
An image analysis method applied to a brain image analysis device including a brain region management interface for displaying brain region information, the method comprising:
responding to an input operation instruction, and determining a brain region to be merged in the brain image to be analyzed; the brain regions to be combined comprise brain regions in different brain regions in the brain image to be analyzed;
acquiring the characteristics of each brain region to be merged, and displaying the characteristics of each brain region to be merged on the brain region management interface;
and carrying out merging operation on each brain region to be merged according to the characteristics of each brain region to be merged to obtain a first target brain region.
In one embodiment, the merging operation is performed on each to-be-merged brain region according to the feature of each to-be-merged brain region to obtain a first target brain region, including:
and carrying out merging operation on each brain region to be merged according to the size of each brain region to be merged and the signal value of each brain region to be merged to obtain the first target brain region.
In one embodiment, the merging operation for each brain region to be merged according to the size of each brain region to be merged and the signal value of each brain region to be merged, to obtain the first target brain region, includes:
determining an average value of the sizes of the brain regions to be combined as the size of the first target brain region, and determining an average value of the signal values of the brain regions to be combined as the signal value of the first target brain region;
and carrying out merging operation on each brain region to be merged according to the size of the first target brain region and the signal value of the first target brain region to obtain the first target brain region.
In one embodiment, the method further comprises:
determining a sample brain region corresponding to each brain region to be merged in a brain region database; the brain region database is a database pre-stored in the brain image analysis device; the brain region database comprises a plurality of sample brain regions, and each sample brain region corresponds to a brain region included in the brain image to be analyzed;
carrying out the merging operation on each sample brain region to obtain a second target brain region;
comparing and analyzing the first target brain area and the second target brain area to obtain an analysis result; the analysis result is used for indicating whether an abnormal area exists in the brain image to be analyzed.
In one embodiment, the comparing the first target brain region and the second target brain region to obtain the analysis result includes:
and comparing and analyzing the first target brain region and the second target brain region according to the size of the first target brain region, the signal value of the first target brain region, the size of the second target brain region and the signal value of the second target brain region to obtain the analysis result.
In one embodiment, the method further comprises:
and comparing and analyzing the sample brain regions with the brain regions to be combined to obtain comparison and analysis results of the brain regions to be combined and the sample brain regions.
In one embodiment, the method further comprises:
receiving a revocation instruction triggered by a user;
and according to the withdrawal instruction, withdrawing the merging operation to obtain each brain region to be merged, and displaying each brain region to be merged on the brain region management interface.
An image analysis apparatus, the apparatus comprising:
the determining module is used for determining brain regions to be merged in the brain images to be analyzed according to operation instructions input by a user; the brain regions to be combined comprise brain regions in different brain regions in the brain image to be analyzed;
the acquisition module is used for acquiring the characteristics of each brain region to be combined and displaying the characteristics of each brain region to be combined on the brain region management interface;
the first merging module is used for merging the brain regions to be merged according to the characteristics of the brain regions to be merged to obtain a first target brain region.
A computer device comprising a memory storing a computer program and a processor which when executing the computer program performs the steps of:
responding to an input operation instruction, and determining a brain region to be merged in the brain image to be analyzed; the brain regions to be combined comprise brain regions in different brain regions in the brain image to be analyzed;
acquiring the characteristics of each brain region to be merged, and displaying the characteristics of each brain region to be merged on the brain region management interface;
and carrying out merging operation on each brain region to be merged according to the characteristics of each brain region to be merged to obtain a first target brain region.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
responding to an input operation instruction, and determining a brain region to be merged in the brain image to be analyzed; the brain regions to be combined comprise brain regions in different brain regions in the brain image to be analyzed;
acquiring the characteristics of each brain region to be merged, and displaying the characteristics of each brain region to be merged on the brain region management interface;
and carrying out merging operation on each brain region to be merged according to the characteristics of each brain region to be merged to obtain a first target brain region.
According to the image analysis method, the device, the computer equipment and the storage medium, the brain areas to be combined can be determined in the brain image to be analyzed through responding to the input operation instruction, wherein the brain areas to be combined comprise brain areas in different brain areas in the brain image to be analyzed, so that the characteristics of the brain areas to be combined can be obtained, the brain areas to be combined can be accurately combined according to the characteristics of the brain areas to be combined, and a first target brain area with higher accuracy is obtained.
Drawings
FIG. 1 is a diagram of an application environment for an image analysis method in one embodiment;
FIG. 2 is a flow chart of an image analysis method according to an embodiment;
FIG. 3 is a flow chart of an image analysis method according to another embodiment;
FIG. 4 is a flow chart of an image analysis method according to another embodiment;
FIG. 4a is a flow chart of an image analysis method according to one embodiment;
FIG. 5 is a flow chart of an image analysis method according to another embodiment;
fig. 6 is a block diagram showing the structure of an image analysis apparatus in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
The image analysis method provided by the embodiment of the application can be applied to the brain image analysis device shown in fig. 1. The brain image analysis device comprises a processor, a memory, and a computer program stored in the memory, wherein the processor can execute the steps of the following method embodiments when executing the computer program. Optionally, the brain image analysis device may further comprise a network interface, a display screen and an input means. Optionally, the image analysis device may further comprise a database for storing the sample brain region. Wherein the processor of the brain image analysis device is configured to provide computing and control capabilities. The memory of the brain image analysis device includes a nonvolatile storage medium storing an operating system and a computer program, and an internal memory. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the brain image analysis device is used for communicating with an external terminal through a network connection. Optionally, the brain image analysis device may be a server, may be a personal computer, may also be a personal digital assistant, may also be other terminal devices, such as a tablet computer, a mobile phone, etc., and may also be a cloud or remote server.
In one embodiment, as shown in fig. 2, an image analysis method is provided, which is exemplified by application of the method to the brain image analysis device in fig. 1, and includes the steps of:
s201, determining brain regions to be merged in brain images to be analyzed in response to input operation instructions; the brain regions to be merged comprise brain regions in different brain regions in the brain image to be analyzed.
Specifically, the brain image analysis device determines brain regions to be merged in the brain image to be analyzed in response to an operation instruction input by a user. The brain image to be analyzed may be a computed tomography (Computed Tomography, CT), a magnetic resonance image (Magnetic Resonance Image, MRI), a positron emission tomography (Positron Emission Computed Tomography, PET), a magnetic resonance TOF sequence image, or a digital subtraction angiography image (Digital Subtraction Angiography, DSA), etc. Wherein the brain regions to be merged comprise brain regions in different brain regions in the brain image to be analyzed. The brain image analysis device comprises a brain region management interface which is used for displaying brain region information. Optionally, the brain image analysis device may analyze an operation instruction input by a user to obtain an identifier of a brain region to be combined included in the operation instruction, so as to determine the brain region to be combined in the brain image to be analyzed. Optionally, the brain image analysis device may label the selected brain regions to be merged in the brain image to be analyzed, and determine the brain regions to be merged. Alternatively, the brain regions to be merged may be all brain regions of the left brain, all brain regions of the right brain, or both brain regions of the left brain and brain regions of the right brain.
S202, obtaining the characteristics of each brain region to be merged, and displaying the characteristics of each brain region to be merged on a brain region management interface.
Specifically, the brain image analysis device acquires the characteristics of each brain region to be merged, and displays the characteristics of each brain region to be merged on a brain region management interface of the brain image analysis device. Optionally, the brain image analysis device may analyze each brain region to be merged by using existing analysis software thereof, so as to obtain characteristics of each brain region to be merged. Optionally, the brain image analysis device may display the features of each brain region to be merged on the upper right side of each brain region to be merged on the brain region management interface, or may display the features of each brain region to be merged on the upper left side of each brain region to be merged, where in this embodiment, the display position of the features of each brain region to be merged is not limited.
S203, merging the brain regions to be merged according to the characteristics of the brain regions to be merged to obtain a first target brain region.
Specifically, the brain image analysis device performs merging operation on each brain region to be merged according to the characteristics of each brain region to be merged, so as to obtain a first target brain region. Optionally, the feature of the brain regions to be merged may be the size of the brain regions to be merged, or may be a signal value of the brain regions to be merged, that is, the brain image analysis device may perform merging operation on each brain region to be merged according to the size of each brain region to be merged to obtain the first target brain region, or may perform merging operation on each brain region to be merged according to the signal value of each brain region to be merged to obtain the first target brain region. When the brain image to be analyzed is a CT image, the signal value of the brain region to be combined is represented by a CT value; when the brain image to be analyzed is an MRI image, the signal value of the brain region to be combined can be represented by an echo signal intensity value; when the brain image to be analyzed is a PET image, the signal value of the brain region to be combined is a data standard uptake value (standard uptake value, SUV), and SUV refers to the radioactivity of the imaging agent taken by local tissues and the average injection activity of the whole body. It should be noted that, by performing merging operation on the brain regions to be merged, the obtained first target brain region can obtain relatively rich image information, for example, when the brain regions to be merged are taken as adjacent brain regions, for example, temporal lobe epilepsy occurs, the hippocampus should have relatively large asymmetry, but according to the conventional classification standard, the hippocampus is divided into a hippocampus and a parahippocampus, when the asymmetries of the two cerebellum regions are seen separately, the severity of the two cerebellum regions cannot be highlighted, when the hippocampus and the parahippocampus are merged, the asymmetries of the two brain regions can be obviously displayed, and when the non-uniqueness of the hippocampus is analyzed; for another example, in a cerebral neurodegenerative disease, frontotemporal dementia is a particularly large proportion, but according to conventional classification standards, the frontotemporal dementia is divided into 10 cerebellar regions (10 each on the left and right), and the temporal lobe is divided into 10 cerebellar regions (10 each on the left and right), but in the case where the temporal lobe and the frontal lobe are integral when the user wants to see, it is necessary to directly merge the cerebellar regions into a middle cerebral region; for another example, since the brains are symmetrical structures, such as left and right anterior wedge lobes, the ratio analysis often used in the analysis of dementia requires the ratio of the entire (left + right) anterior wedge lobe to the cerebellum as an evaluation parameter, and the left anterior wedge lobe and the right anterior wedge lobe are combined.
In the image analysis method, the brain image analysis equipment can determine the brain regions to be combined in the brain image to be analyzed by responding to the input operation instruction, wherein the brain regions to be combined comprise brain regions in different brain regions in the brain image to be analyzed, so that the brain image analysis equipment can accurately combine the brain regions to be combined according to the characteristics of the brain regions to be combined by acquiring the characteristics of the brain regions to be combined, thereby obtaining a first target brain region with higher accuracy.
In the above scenario where the merging operation is performed on each brain region to be merged according to the characteristics of each brain region to be merged to obtain the first target brain region, in one embodiment, the step S203 includes: and carrying out merging operation on each brain region to be merged according to the size of each brain region to be merged and the signal value of each brain region to be merged, so as to obtain a first target brain region.
Specifically, the brain image analysis device performs merging operation on each brain region to be merged according to the size of each brain region to be merged and the signal value of each brain region to be merged, so as to obtain a first target brain region. Optionally, the brain image analysis device may determine the sum of the sizes of the brain regions to be merged as the size of the first target brain region, determine the sum of the signal values of the brain regions to be merged as the signal value of the first target brain region, and further perform merging operation on each brain region to be merged according to the sum of the sizes of the brain regions to be merged and the sum of the signal values of the brain regions to be merged, to obtain the first target brain region.
In this embodiment, since the brain image analysis device performs the merging operation on each brain region to be merged according to the size of each brain region to be merged and the signal value of each brain region to be merged, the accuracy of the merging operation on each brain region to be merged is ensured, and the obtained first target brain region is accurate, so that the accuracy of the obtained first target brain region is improved.
In the above scenario where the merging operation is performed on each brain region to be merged according to the size of each brain region to be merged and the signal value of each brain region to be merged to obtain the first target brain region, the brain image analysis device may determine the average value of the sizes of each brain region to be merged as the size of the first target brain region, and determine the average value of the signal values of each brain region to be merged as the signal value of the first target brain region. In one embodiment, as shown in fig. 3, the merging operation is performed on each brain region to be merged according to the size of each brain region to be merged and the signal value of each brain region to be merged, so as to obtain a first target brain region, which includes:
s301, determining an average value of the sizes of the brain regions to be merged as a size of a first target brain region, and determining an average value of the signal values of the brain regions to be merged as a signal value of the first target brain region.
Specifically, the brain image analysis device determines an average value of the sizes of the brain regions to be merged as the size of the first target brain region, and determines an average value of the signal values of the brain regions to be merged as the signal value of the first target brain region. Alternatively, the average value of the sizes of the brain regions to be merged may be a weighted average value of the sizes of the brain regions to be merged, or may be a geometric average value of the sizes of the brain regions to be merged, and similarly, the average value of the signal values of the brain regions to be merged may be a weighted average value of the signal values of the brain regions to be merged, or may be a geometric average value of the signal values of the brain regions to be merged.
S302, merging the brain regions to be merged according to the size of the first target brain region and the signal value of the first target brain region to obtain the first target brain region.
Specifically, the brain image analysis device performs merging operation on each to-be-merged brain region according to the determined size of the first target brain region and the determined signal value of the first target brain region to obtain the first target brain region, that is, the brain image analysis device determines the average value of the sizes of each to-be-merged brain region as the size of the first target brain region, determines the average value of the signal values of each to-be-merged brain region as the signal value of the first target brain region, and performs merging operation on each to-be-merged brain region according to the average value of the sizes of each to-be-merged brain region and the average value of the signal values of each to-be-merged brain region to obtain the first target brain region.
In this embodiment, since the process of obtaining the average value of the sizes of the brain regions to be merged and the average value of the signal values of the brain regions to be merged by the brain image analysis device is relatively simple, the efficiency of obtaining the average value of the sizes of the brain regions to be merged and the average value of the signal values of the brain regions to be merged by the brain image analysis device is improved, so that the brain image analysis device can quickly determine the size of the first target brain region and the signal value of the first target brain region, and thus the brain image analysis device can quickly merge the brain regions to be merged according to the determined size of the first target brain region and the determined signal value of the first target brain region to obtain the first target brain region, thereby improving the efficiency of obtaining the first target brain region.
In some scenes, the brain image analysis device may further merge the sample brain regions stored in the brain region database, and further compare and analyze the merged sample brain region with the obtained first target brain region, so as to obtain an analysis result for indicating whether an abnormal region exists in the brain image to be analyzed. In one embodiment, as shown in fig. 4, the method further includes:
s401, determining a sample brain region corresponding to each brain region to be merged in a brain region database; the brain region database is a database stored in the brain image analysis device in advance; the brain region database comprises a plurality of sample brain regions, and each sample brain region corresponds to a brain region included in the brain image to be analyzed.
Specifically, the brain image analysis device determines, in the brain region database, a sample brain region corresponding to each of the above-described brain regions to be merged. Wherein the brain region database is a database stored in the brain image analysis device in advance; the brain region database comprises a plurality of sample brain regions, and each sample brain region corresponds to a brain region included in a brain image to be analyzed. Optionally, the brain image analysis device may match each brain region to be merged with a plurality of sample brain regions included in the brain region database one by one according to the shape of each brain region, so as to determine a sample brain region corresponding to each brain region to be merged in the brain region database, or determine a sample brain region identical to the signal value of each brain region to be merged in the brain region database according to the signal value of each brain region to be merged, so as to obtain a sample brain region corresponding to each brain region to be merged. It should be noted that, the plurality of sample brain regions included in the brain region database may be brain regions corresponding to people of different ages, or brain regions corresponding to people of different sexes.
S402, merging the brain regions of the samples to obtain a second target brain region.
Specifically, the brain image analysis device performs merging operation on the determined sample brain regions corresponding to the brain regions to be merged to obtain a second target brain region. Optionally, the brain image analysis device may determine an average value of sizes of the sample brain regions corresponding to the brain regions to be merged as a size of the second target brain region, determine an average value of signal values of the sample brain regions corresponding to the brain regions to be merged as a signal value of the second target brain region, and merge each sample brain region according to the determined size of the second target brain region and the determined signal value of the second target brain region to obtain the second target brain region.
S403, comparing and analyzing the first target brain region and the second target brain region to obtain an analysis result; the analysis result is used for indicating whether an abnormal area exists in the brain image to be analyzed.
Specifically, the brain image analysis device performs comparison analysis on the obtained first target brain region and second target brain region to obtain an analysis result, wherein the analysis result is used for indicating whether an abnormal region exists in the brain image to be analyzed. Alternatively, the analysis result of the first target brain region and the second target brain region obtained by the brain image analysis device may be that no abnormal region exists in the brain image to be analyzed, or that an abnormal region exists in the brain image to be analyzed. Optionally, the brain image analysis device may compare and analyze the shape of the first target brain region with the shape of the second target brain region, determine whether the shapes of the first target brain region and the second target brain region are consistent, if not, compare and analyze the inconsistent area to determine whether an abnormal area exists in the brain image to be analyzed, and also compare and analyze the size of the first target brain region with the size of the second target brain region to determine whether the size of the first target brain region and the size of the second target brain region are consistent, and if not, compare and analyze the area with larger difference between the sizes of the first target brain region and the second target brain region to determine whether an abnormal area exists in the brain image to be analyzed.
As shown in fig. 4a, in the image analysis method provided in this embodiment, the size and signal value of the first target brain region may be obtained according to the size and signal value of each brain region to be merged, the average size and signal average value of the second target brain region may be obtained according to the average size and signal average value of the sample brain regions corresponding to each brain region to be merged in the brain region database, and the size and signal value of each brain region to be merged may be compared with the average size and signal average value of the sample brain regions corresponding to each brain region to be merged in the brain region database, so as to obtain the difference between the first target brain region and the second target brain region, and the difference between the non-merged brain region in the brain image to be analyzed and the corresponding sample brain region in the database.
In this embodiment, the process of determining, in the brain region database, the sample brain regions corresponding to the brain regions to be merged by the brain image analysis device is very simple, and the sample brain regions corresponding to the brain regions to be merged can be quickly determined, so that merging operation can be quickly performed on the determined sample brain regions to obtain the second target brain region, and the efficiency of obtaining the second target brain region is improved.
In the above scenario where the comparison analysis is performed on the first target brain region and the second target brain region to obtain the analysis result indicating whether the abnormal region exists in the brain image to be analyzed, in one embodiment, the step S403 includes: and comparing and analyzing the first target brain region and the second target brain region according to the size of the first target brain region, the signal value of the first target brain region, the size of the second target brain region and the signal value of the second target brain region to obtain an analysis result.
Specifically, the brain image analysis device performs comparison analysis on the first target brain region and the second target brain region according to the size of the first target brain region, the signal value of the first target brain region, the size of the second target brain region and the signal value of the second target brain region, so as to obtain the analysis result. Alternatively, the brain image analysis device may compare the size of the first target brain region with the size of the second target brain region, and compare the signal value of the first target brain region with the signal value of the second target brain region, to obtain the analysis result.
In this embodiment, the brain image analysis device can rapidly compare and analyze the first target brain region and the second target brain region according to the size of the first target brain region, the signal value of the first target brain region, the size of the second target brain region and the signal value of the second target brain region, so that the analysis results of the first target brain region and the second target brain region can be rapidly obtained, and the efficiency of obtaining the analysis results of the first target brain region and the second target brain region is improved.
In some scenarios, the brain image analysis device may further compare and analyze a single brain region in the brain region database with a single brain region in the brain image to be analyzed, and on the basis of the above embodiment, in one embodiment, the above method further includes: and comparing and analyzing the sample brain region and the brain region to be combined to obtain a comparison and analysis result of the brain region to be combined and the sample brain region.
Specifically, the brain image analysis device compares and analyzes the sample brain region in the brain region database with each brain region to be combined in the brain image to be analyzed, and obtains comparison and analysis results of each brain region to be combined and the sample brain region in the brain region database. Optionally, the brain image analysis device may compare and analyze the sizes of the sample brain regions in the brain region database and the brain regions to be combined in the brain image to be analyzed to obtain comparison and analysis results of the sample brain regions in the brain region database and the brain regions to be combined, and may also compare and analyze the signal values of the sample brain regions in the brain region database and the brain regions to be combined in the brain image to be analyzed to obtain comparison and analysis results of the sample brain regions in the brain region database and the brain regions to be combined.
In this embodiment, the process of comparing and analyzing the sample brain region in the brain region database with each brain region to be combined in the brain image to be analyzed by the brain image analysis device is very simple, and can quickly obtain the comparison and analysis result of each brain region to be combined with the sample brain region, thereby improving the efficiency of obtaining the comparison and analysis result of each brain region to be combined with the sample brain region.
In some scenarios, the brain image analysis device may further cancel the merging operation on the first target brain region to obtain each brain region to be merged, and on the basis of the above embodiment, in one embodiment, as shown in fig. 5, the method further includes:
s501, receiving a user-triggered revocation instruction.
Specifically, the brain image analysis device receives a user-triggered revocation instruction. Alternatively, the undo instruction may be triggered by the user on a display screen of the brain image analysis device. Optionally, the revocation instruction may be used to instruct the brain image analysis device to revoke all merging operations on the first target brain region, and may also be used to instruct the brain image analysis device to revoke a partial merging operation on the first target brain region.
S502, according to the withdrawal instruction, withdrawing the merging operation to obtain each brain region to be merged, and displaying each brain region to be merged on a brain region management interface.
Specifically, according to the withdrawal instruction, the brain image analysis device withdraws the merging operation of each brain region to be merged to obtain each brain region to be merged, and displays each brain region to be merged on a brain region management interface of the brain image analysis device. Optionally, the brain image analysis device may first select the first target brain region, and then cancel the merging operation on the first target brain region according to the cancel instruction, so as to obtain each brain region to be merged.
In this embodiment, according to a revocation instruction triggered by a user, the brain image analysis device can rapidly revoke merging operations performed on the first target brain regions to obtain each to-be-merged brain region corresponding to the first target brain region, so that efficiency of obtaining each to-be-merged brain region corresponding to the first target brain region is improved, further, each to-be-merged brain region obtained by displaying on a brain region management interface of the brain image analysis device can be intuitively checked by the user.
It should be understood that, although the steps in the flowcharts of fig. 2-5 are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 2-5 may include multiple steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor does the order in which the steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the steps or stages in other steps or other steps.
In one embodiment, as shown in fig. 6, there is provided an image analysis apparatus including: the device comprises a determining module, an acquiring module and a first merging module, wherein:
the determining module is used for determining brain regions to be merged in the brain images to be analyzed according to the operation instructions input by the user; the brain regions to be merged comprise brain regions in different brain regions in the brain image to be analyzed.
The acquisition module is used for acquiring the characteristics of each brain region to be merged and displaying the characteristics of each brain region to be merged on the brain region management interface.
And the first merging module is used for merging the brain regions to be merged according to the characteristics of the brain regions to be merged to obtain a first target brain region.
The image analysis device provided in this embodiment may execute the above method embodiment, and its implementation principle and technical effects are similar, and will not be described herein.
On the basis of the foregoing embodiment, optionally, the first merging module includes: a merging unit in which:
and the merging unit is used for merging the brain regions to be merged according to the size of the brain regions to be merged and the signal value of the brain regions to be merged to obtain a first target brain region.
The image analysis device provided in this embodiment may execute the above method embodiment, and its implementation principle and technical effects are similar, and will not be described herein.
On the basis of the above embodiment, optionally, the merging unit is specifically configured to determine an average value of sizes of the brain regions to be merged as a size of the first target brain region, and determine an average value of signal values of the brain regions to be merged as a signal value of the first target brain region; and carrying out merging operation on each brain region to be merged according to the size of the first target brain region and the signal value of the first target brain region to obtain the first target brain region.
The image analysis device provided in this embodiment may execute the above method embodiment, and its implementation principle and technical effects are similar, and will not be described herein.
On the basis of the above embodiment, optionally, the above apparatus further includes: the device comprises a determining module, a second combining module and a first analyzing module, wherein:
the determining module is used for determining a sample brain region corresponding to each brain region to be merged in the brain region database; the brain region database is a database stored in the brain image analysis device in advance; the brain region database comprises a plurality of sample brain regions, and each sample brain region corresponds to a brain region included in the brain image to be analyzed.
And the second merging module is used for merging the brain regions of the samples to obtain a second target brain region.
The first analysis module is used for comparing and analyzing the first target brain region and the second target brain region to obtain an analysis result; the analysis result is used for indicating whether an abnormal area exists in the brain image to be analyzed.
The image analysis device provided in this embodiment may execute the above method embodiment, and its implementation principle and technical effects are similar, and will not be described herein.
On the basis of the above embodiment, optionally, the first analysis module includes: an analysis unit, wherein:
the analysis unit is used for comparing and analyzing the first target brain region and the second target brain region according to the size of the first target brain region, the signal value of the first target brain region, the size of the second target brain region and the signal value of the second target brain region, and obtaining an analysis result.
The image analysis device provided in this embodiment may execute the above method embodiment, and its implementation principle and technical effects are similar, and will not be described herein.
On the basis of the above embodiment, optionally, the above apparatus further includes: a second analysis module, wherein:
and the second analysis module is used for comparing and analyzing the sample brain regions with the brain regions to be combined to obtain comparison and analysis results of the brain regions to be combined and the sample brain regions.
The image analysis device provided in this embodiment may execute the above method embodiment, and its implementation principle and technical effects are similar, and will not be described herein.
On the basis of the above embodiment, optionally, the above apparatus further includes: a receiving module and a revocation module, wherein:
and the receiving module is used for receiving the revocation instruction triggered by the user.
And the revocation module is used for revoke the merging operation according to the revocation instruction to obtain each brain region to be merged, and displaying each brain region to be merged on the brain region management interface.
The image analysis device provided in this embodiment may execute the above method embodiment, and its implementation principle and technical effects are similar, and will not be described herein.
For specific limitations of the image analysis apparatus, reference may be made to the above limitations of the image analysis method, and no further description is given here. The respective modules in the image analysis apparatus described above may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, there is provided a brain image analysis device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
responding to the input operation instruction, and determining a brain region to be merged in the brain image to be analyzed; the brain regions to be merged comprise brain regions in different brain regions in the brain image to be analyzed;
acquiring the characteristics of each brain region to be merged, and displaying the characteristics of each brain region to be merged on a brain region management interface;
and carrying out merging operation on each brain region to be merged according to the characteristics of each brain region to be merged to obtain a first target brain region.
The computer device provided in the foregoing embodiments has similar implementation principles and technical effects to those of the foregoing method embodiments, and will not be described herein in detail.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
responding to the input operation instruction, and determining a brain region to be merged in the brain image to be analyzed; the brain regions to be merged comprise brain regions in different brain regions in the brain image to be analyzed;
acquiring the characteristics of each brain region to be merged, and displaying the characteristics of each brain region to be merged on a brain region management interface;
and carrying out merging operation on each brain region to be merged according to the characteristics of each brain region to be merged to obtain a first target brain region.
The computer readable storage medium provided in the above embodiment has similar principle and technical effects to those of the above method embodiment, and will not be described herein.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, or the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.
Claims (10)
1. An image analysis method applied to a brain image analysis device including a brain region management interface for displaying brain region information, the method comprising:
responding to an input operation instruction, analyzing the operation instruction to obtain an identification of a brain region to be merged, and determining the brain region to be merged in a brain image to be analyzed according to the identification of the brain region to be merged; the brain regions to be combined comprise brain regions in different brain regions in the brain image to be analyzed;
acquiring the characteristics of each brain region to be merged, and displaying the characteristics of each brain region to be merged on the brain region management interface; the characteristics of each brain region to be merged comprise the size of each brain region to be merged and the signal value of each brain region to be merged;
determining an average value of the sizes of the brain regions to be combined as a first target brain region, and determining an average value of the signal values of the brain regions to be combined as the signal value of the first target brain region; according to the size of the first target brain region and the signal value of the first target brain region, merging the brain regions to be merged to obtain the first target brain region; or alternatively, the process may be performed,
determining the sum of the sizes of the brain regions to be merged as the size of a first target brain region, determining the sum of the signal values of the brain regions to be merged as the signal value of the first target brain region, and merging the brain regions to be merged according to the sum of the sizes of the brain regions to be merged and the sum of the signal values of the brain regions to be merged to obtain the first target brain region.
2. The method of claim 1, wherein the average value of the sizes of the brain regions to be merged is a weighted average value of the sizes of the brain regions to be merged or is a geometric average value of the sizes of the brain regions to be merged; the average value of the signal values of the brain regions to be merged is a weighted average value of the signal values of the brain regions to be merged or a geometric average value of the signal values of the brain regions to be merged.
3. The method of claim 2, wherein the brain image to be analyzed comprises any one of a computed tomography image, a magnetic resonance image, a positron emission tomography image, a magnetic resonance TOF sequence image, a digital subtraction angiography image.
4. The method according to claim 1, wherein the method further comprises:
determining a sample brain region corresponding to each brain region to be merged in a brain region database;
carrying out the merging operation on each sample brain region to obtain a second target brain region;
comparing and analyzing the first target brain area and the second target brain area to obtain an analysis result; the analysis result is used for indicating whether an abnormal area exists in the brain image to be analyzed.
5. The method of claim 4, wherein comparing the first target brain region to the second target brain region results in an analysis result comprising:
and comparing and analyzing the first target brain region and the second target brain region according to the size of the first target brain region, the signal value of the first target brain region, the size of the second target brain region and the signal value of the second target brain region to obtain the analysis result.
6. The method according to claim 4, wherein the method further comprises:
and comparing and analyzing the sample brain regions with the brain regions to be combined to obtain comparison and analysis results of the brain regions to be combined and the sample brain regions.
7. The method according to any one of claims 1-6, further comprising:
receiving a revocation instruction triggered by a user;
and according to the withdrawal instruction, withdrawing the merging operation to obtain each brain region to be merged, and displaying each brain region to be merged on the brain region management interface.
8. An image analysis apparatus, the apparatus comprising:
the determining module is used for responding to an input operation instruction, analyzing the operation instruction to obtain an identification of a brain region to be merged, and determining the brain region to be merged in an analysis brain image according to the identification of the brain region to be merged; the brain regions to be combined comprise brain regions in different brain regions in the brain image to be analyzed;
the acquisition module is used for acquiring the characteristics of each brain region to be combined and displaying the characteristics of each brain region to be combined on a brain region management interface; the characteristics of each brain region to be merged comprise the size of each brain region to be merged and the signal value of each brain region to be merged;
the first merging module is used for determining the average value of the sizes of the brain regions to be merged as the size of a first target brain region, and determining the average value of the signal values of the brain regions to be merged as the signal value of the first target brain region; according to the size of the first target brain region and the signal value of the first target brain region, merging the brain regions to be merged to obtain the first target brain region; or alternatively, the process may be performed,
determining the sum of the sizes of the brain regions to be merged as the size of a first target brain region, determining the sum of the signal values of the brain regions to be merged as the signal value of the first target brain region, and merging the brain regions to be merged according to the sum of the sizes of the brain regions to be merged and the sum of the signal values of the brain regions to be merged to obtain the first target brain region.
9. A brain image analysis device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 7 when executing the computer program.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.
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